I am going to be analyzing mortality rates among pregnant individuals and infants and how race affects mortality rate in the United States. The goal is to determine if there are prejudices that are leading to negligence when it comes to pregnant individual and infant.
Rows: 540
Columns: 10
$ `Data As Of` <chr> "10/08/2023", "10/08/2023", "10/08/2023", "10/08/2…
$ Jurisdiction <chr> "United States", "United States", "United States",…
$ Group <chr> "By Total", "By Total", "By Total", "By Total", "B…
$ Subgroup <chr> "Total", "Total", "Total", "Total", "Total", "Tota…
$ `Year of Death` <dbl> 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 20…
$ `Month of Death` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4,…
$ `Time Period` <chr> "12 month-ending", "12 month-ending", "12 month-en…
$ `Month Ending Date` <chr> "01/31/2019", "02/28/2019", "03/31/2019", "04/30/2…
$ `Maternal Deaths` <dbl> 660, 653, 657, 668, 706, 720, 721, 723, 729, 739, …
$ Footnote <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
---
title: "Maternal and Infant Mortality Analysis"
output:
flexdashboard::flex_dashboard:
theme:
version: 4
bootswatch: zephyr
primary: "#F285A6"
orientation: columns
vertical_layout: fill
source_code: embed
---
<style>
.chart-title { /* chart_title */
font-size: 16px;
}
body{ /* Normal */
font: 14px;
}
</style>
```{r setup, include=FALSE}
library(flexdashboard)
library(DT)
```
Maternal Mortality Analysis
===
Column {data-width 250}
-----------------------------------------------------------------------
### The Data
I am going to be analyzing mortality rates among pregnant individuals and infants and how race affects mortality rate in the United States. The goal is to determine if there are prejudices that are leading to negligence when it comes to pregnant individual and infant.
```{r}
pacman::p_load(tidyverse, knitr)
Maternal_deathcount <- read_csv("Maternal_deathcount.csv")
glimpse(Maternal_deathcount)
Maternal_deathcount$Subgroup <- recode(Maternal_deathcount$Subgroup,
"Non-Hispanic American Indian or Alaska Native" = "Native_American",
"Non-Hispanic Asian" = "Asian",
"Non-Hispanic Black" = "Black",
"Non-Hispanic Native Hawaiian or other Pacific Islander" = "Pacific_Isalnder",
"Non-Hispanic White" = "White")
df_race <- Maternal_deathcount %>%
filter(Group == "By Race")
```
Column {data-width=750}
-----------------------------------------------------------------------
```{r drop_lat_long}
Hispanic <- Maternal_deathcount[Maternal_deathcount$Subgroup == "Hispanic" , ]
Native <- Maternal_deathcount[Maternal_deathcount$Subgroup == "Native_American" , ]
Asian <- Maternal_deathcount[Maternal_deathcount$Subgroup == "Asian" , ]
Black <- Maternal_deathcount[Maternal_deathcount$Subgroup == "Black" , ]
White <- Maternal_deathcount[Maternal_deathcount$Subgroup == "White" , ]
Race <- Maternal_deathcount[Maternal_deathcount$Group == "By Race and Hispanic origin" , ]
```
### Distribution of Race and Maternal Deaths.
```{r maternal_data}
Death_Count <- Maternal_deathcount %>%
group_by(Subgroup) %>%
summarize(Death = sum(`Maternal Deaths`, na.rm=T))
```
```{r race_v_deathcount}
Death_Count <- Death_Count[-c(1,2,9,10),]
datatable(Death_Count, colnames = c("Race", "Total Death"))
```
Infant Death Analysis
===
column {.tabset data-width=550}
---
### Distribution of Race and Infant Death
```{r race_v_infantdeathcount}
```